ARTIFICIAL INTELLIGENCE IN HEALTHCARE: REVOLUTIONIZING DIAGNOSIS AND TREATMENT THROUGH MACHINE LEARNING

Artificial intelligence (AI), particularly machine learning (ML), is rapidly transforming the healthcare landscape. This paper explores the profound impact of AI in healthcare, focusing on its application in revolutionizing diagnosis and treatment. We delve into the core principles of ML and its various subfields relevant to healthcare, including supervised, unsupervised, and reinforcement learning. Further, we examine specific examples of how AI-powered tools are being implemented to enhance diagnostic accuracy, personalize treatment plans, predict disease outbreaks, and improve patient outcomes. Challenges and ethical considerations associated with AI integration in healthcare are also discussed, highlighting the need for a responsible and equitable approach to its development and deployment. Finally, we explore future trends and potential applications of AI in healthcare, emphasizing its role in shaping the future of medicine.

Authors

Publication Details

Journal
New Healthcare Advancements and Explorations
Published
2024-12-27
DOI
https://doi.org/10.64347/3066-2591/nhae.012
Primary Topic
Healthcare Systems and Public Health
Type
article
Field-Weighted Citation Impact
0.00
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article

ARTIFICIAL INTELLIGENCE IN HEALTHCARE: REVOLUTIONIZING DIAGNOSIS AND TREATMENT THROUGH MACHINE LEARNING

OKECHUKWU CHIDOLUO VITUS
New Healthcare Advancements and Explorations
Healthcare Systems and Public Health
article

ARTIFICIAL INTELLIGENCE IN HEALTHCARE: REVOLUTIONIZING DIAGNOSIS AND TREATMENT THROUGH MACHINE LEARNING

OKECHUKWU CHIDOLUO VITUS
article en

Abstract

Artificial intelligence (AI), particularly machine learning (ML), is rapidly transforming the healthcare landscape. This paper explores the profound impact of AI in healthcare, focusing on its application in revolutionizing diagnosis and treatment. We delve into the core principles of ML and its various subfields relevant to healthcare, including supervised, unsupervised, and reinforcement learning. Further, we examine specific examples of how AI-powered tools are being implemented to enhance diagnostic accuracy, personalize treatment plans, predict disease outbreaks, and improve patient outcomes. Challenges and ethical considerations associated with AI integration in healthcare are also discussed, highlighting the need for a responsible and equitable approach to its development and deployment. Finally, we explore future trends and potential applications of AI in healthcare, emphasizing its role in shaping the future of medicine.

New Healthcare Advancements and ExplorationsVol. 01(03)
Openalex Percentile: Top 61%
Healthcare Systems and Public Health
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